U.S. patent application number 14/938582 was filed with the patent office on 2017-05-11 for global communication and control.
The applicant listed for this patent is UT Battelle, LLC. Invention is credited to Andrew Harter, Erik Kabela, Brad Stinson.
Application Number | 20170134497 14/938582 |
Document ID | / |
Family ID | 58663977 |
Filed Date | 2017-05-11 |
United States Patent
Application |
20170134497 |
Kind Code |
A1 |
Harter; Andrew ; et
al. |
May 11, 2017 |
GLOBAL COMMUNICATION AND CONTROL
Abstract
A process detects media dispersion. The process detects the
dispersion of contaminants through distributed remote sensor
platforms that connect one or more sensors on a remote device. The
process transmits detection data from the distributed remote sensor
platform to a radiation tolerant satellite router. A gateway
connects the radiation tolerant satellite router to a hardware
server and converts the detection data to a compatible form with a
protocol used by a hardware server. The process generates a plume
model in response to the detection data and meteorological data
that models dispersion plumes and activates and deactivates
selected sensors in response to a forecasted to dispersion
area.
Inventors: |
Harter; Andrew; (Oak Ridge,
TN) ; Stinson; Brad; (Oak Ridge, TN) ; Kabela;
Erik; (Oak Ridge, TN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
UT Battelle, LLC |
Oak Ridge |
TN |
US |
|
|
Family ID: |
58663977 |
Appl. No.: |
14/938582 |
Filed: |
November 11, 2015 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 33/0004 20130101;
H04L 67/34 20130101; H04L 67/12 20130101; H04L 67/2823
20130101 |
International
Class: |
H04L 29/08 20060101
H04L029/08; G01N 33/00 20060101 G01N033/00; G06F 17/50 20060101
G06F017/50; H04B 7/185 20060101 H04B007/185 |
Goverment Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND
DEVELOPMENT
[0001] This invention was made with United States government
support under Contract No. DE-ACO5-000R22725 awarded by the United
States Department of Energy. The United States government has
certain rights in the invention.
Claims
1. A global communication and control process comprising: detecting
the dispersion of contaminants through a plurality of distributed
remote sensor platforms connected one or more sensors on a remote
device; transmitting detection data from the distributed remote
sensor platform to a radiation tolerant satellite router;
processing the detection data at a gateway that connects the
radiation tolerant satellite router to a gateway that converts the
detection data to a from compatible with a protocol used by a
hardware server and transferring the detection data to the hardware
server; generating a plume model in response to the detection data
and meteorological data that models dispersion plumes; and
activating selected one or more sensors in response to a forecasted
dispersion area generated from the plume model.
2. The process if claim 1 where the process deactivates selected
one or more sensors in response to a forecasted dispersion area
generated from the plume model.
3. The process of claim 1 where one or more sensors comprise static
or mobile sensors and virtual sensors that are generated from a
virtual configuration file that generate the sensors and connect
the sensors to one or more of the plurality of distributed remote
sensor platforms.
4. The process of claim 1 where the one or more sensors are mobile
sensors that are a unitary part of an unmanned aerial vehicle.
5. The process of claim 4 where the activation of the selected one
or more sensors comprises configuring the one or more sensors in
response to the generated plume model.
6. The process of claim 1 where the generation of the plume occurs
at least as fast as the same rate as the detection data is received
at the gateway enabling the process to direct and control the
selected one or more sensors in real time.
7. The process of claim 1 where the communication between the
radiation tolerant satellite router and the gateway occurs through
a packet switch protocol like an Internet protocol.
8. The process of claim 7 where the protocol does not resend
replacement packets when packets are lost.
9. The process of claim 8 where the communication protocol executes
a modified linear network coding to generate replacement packets
for packets lost.
10. The process of claim 9 where the communication protocol
transmits an algebraic equation that describes a series of
packets.
11. The method of claim 8 where communication protocol executes a
random linear coding that combines several packets into a same
sized packet.
12. The method of claim 1 further comprising regenerating the plume
model in response to the detection data and meteorological data
that models dispersion plumes and detection data received from the
one or more sensors that were activated in response to the
forecasted dispersion area generated from a prior plume model.
13. The method of claim 1 where the detection data samples an
aerosol or sample of air.
14. The method of claim 1 where the one or more sensors comprises
mobile sensors, buoyed sensors, and static sensors.
15. The method of claim 1 where at least some of the one or more
sensors are integrated into a UAV.
16. A global communication and control process comprising:
detecting the dispersion of contaminants through a plurality of
distributed remote sensor platforms connected to one or more
sensors on a remote device; transmitting detection data from the
distributed remote sensor platform to a radiation tolerant
satellite router; processing the detection data at a gateway that
connects the radiation tolerant satellite router to a gateway that
converts the detection data to a form compatible with a protocol
used by a hardware server and transferring the detection data to
the hardware server; generating a plume model in response to the
detection data and meteorological data that models dispersion
plumes; and activating selected one or more sensors in response to
a forecasted dispersion area generated from the plume model; where
the detecting act, the transmitting act, the processing act, the
generating act, and the activating act occurs autonomously in
real-time without human intervention.
17. An autonomous global communication and control system
comprising: a central processing unit processing executable code
accessed from a random access memory, in which the executable code:
detects the dispersion of contaminants through a plurality of
distributed remote sensor platforms connected to one or more
sensors on a remote device; transmits detection data from the
distributed remote sensor platform to a radiation tolerant
satellite router; processes the detection data at a gateway that
connects the radiation tolerant satellite router to a gateway that
converts the detection data to a form compatible with a protocol
used by a hardware server and transferring the detection data to
the hardware server; generates a plume model in response to the
detection data and meteorological data that models dispersion
plumes; and activates selected one or more sensors in response to a
forecasted dispersion area generated from the plume model.
Description
BACKGROUND
[0002] 3. Technical Field
[0003] This disclosure relates to remote monitoring and more
specifically to systems/processes that acquire sensor data on a
global scale and forecast dispersions.
[0004] 4. Related Art
[0005] Environmental monitoring can protect the public and the
environment from contaminants and pathogens that are released into
a variety of media including air, soil, and water. Some pollutants
are by-products of vehicle emissions, power plants, refineries,
industrial and laboratory processes or intentionally released to
harm the public and the environment. Soil and water contaminants
may be microbiological (e.g., coliform), radioactive (e.g.,
tritium), inorganic (e.g., arsenic), synthetic organic (e.g.,
pesticides), and volatile organic compounds (e.g., benzene). Some
contaminants can persist for many years and migrate through large
regions of soil until they reach water resources, where they may
present an ecological or a health threat.
[0006] There are regulations on the concentrations of many
environmental contaminants in air and water. However, current
monitoring methods are costly, time-intensive, geographically
restricted, and limited by sampling and analytical techniques.
Currently, the ability to deploy and use sensors in global networks
is uncertain due to global and technological barriers. A need
exists for accurate inexpensive long-term global monitoring
platform that can monitor contaminants using sensors that may be
configured, operated, and harvested on site or in position.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] The patent or application file contains at least one drawing
executed in color. Copies of this patent or patent application
publication with color drawing(s) will be provided by the Office
upon request and payment of the necessary fee.
[0008] FIG. 1 is a global plug-and-play automated configurable
sensor control and data acquisition platform.
[0009] FIG. 2 is a graphic representation of an exemplary remote
sensor platform (RSP) shown in its geographical location.
[0010] FIG. 3 is a graphic representation of the RSP of FIG. 2 and
an exemplary log.
[0011] FIG. 4 is a graphic representation of the RSP of FIG. 2 and
exemplary software enabled controls.
[0012] FIG. 5 is a graphic representation of the RSP of FIG. 2 and
an exemplary log.
[0013] FIG. 6 shows an exemplary RSP sampling with active real-time
weather data.
[0014] FIG. 7 shows an exemplary RSP (in red), weather stations (in
blue), and a source location (in green).
[0015] FIG. 8 is a graphic of a plume projected at the source
location of FIG. 7.
[0016] FIG. 9 shows the plume's dispersion of FIG. 8.
[0017] FIG. 10 shows a target monitoring area and an unmanned
aerial vehicle (UAV).
[0018] FIG. 11 is exemplary remote monitoring process.
[0019] FIG. 12 is an alternate global plug-and-play automated
configurable sensor control and data acquisition platform.
[0020] FIG. 13 is an alternate global plug-and-play automated
configurable sensor control and data acquisition platform.
[0021] FIG. 14 is an exemplary RSP.
[0022] FIG. 15 is an exemplary RSP reduced to practice.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0023] This disclosure describes a remote monitoring architecture
that may acquire sensor data on a global scale. The system and
process (herein referred to as the system) is fully or partially
autonomous. The sampling services it renders enable global sensor,
remote data collection, and remote satellite control through
wireless communication. The system improves wireless bandwidth
throughput by an order of magnitude that further supports
encryption and authentication without adding base stations or
spectrum. It provides global coverage across oceans, continents,
airways, and the polar regions of the earth.
[0024] FIG. 1 illustrates a global plug-and-play automated
configurable sensor control and data acquisition platform. The
system 100 expedites message delivery through a hardware radiation
tolerant IP router (satellite router) 102 that orbits the earth.
The satellite router 102 receives transmitted messages from remote
sensor (hardware) platforms (RSP) and wirelessly transmits them to
a hardware gateway 104. The gateway 104 interconnects wireless and
tangible networks such as a local area network to the satellite
router 102. The gateway 104 executes protocol conversions between
the satellite router 102 and the wireless/tangible networks, data
translations, data conversions, and performs message handling. A
hardware information repository and intelligent server 106 tracks
and traces communication with one or more RSPs and hardware clients
110. The information repository and intelligent server 106
captures, stores, and analyzes event data at the unit or lot level
as data is collected from a local or a remote global area. Once
captured the data is processed to detect contaminants, model
plumes, and enable and configure additional RSPs and/or sensors
that can track and forecast the flow of materials such as gases and
aerosols that comprise the plumes. As the plume spreads, the system
100 activates sensors in the projected contaminants paths, harvests
data from RSPs and meteorological stations in or near its projected
path, and adjusts the plume model to help identify the gases and
aerosols (and/or other media) and the paths that it is predicted to
follow. The system's smart RSPs and operations can match the real
time characteristics of the event allowing the system to respond to
a dispersion as it occurs (e.g., at the same rate data is received
or at least as fast as that rate or substantially at that rate),
positioning, enabling, or generating virtual sensors on RSP's in
its pojected path, disabling RSP's no longer in its path, while
making corrections such as modeling corrections based on
measurements, analytics, and forecasts. When errors occur the
information repository and intelligent server 106 may automatically
execute diagnostic software that may include a diagnostics program
that performs network diagnostics and continuity evaluations of the
communication links and operations of remote RSPs. When errors are
detected the system 100 logs the error and reports the error
condition electronically such as through messaging or electronic
mail and attempts to mediate the error by executing software
diagnostic routines, executing software resets, executing hardware
resets, power cycling, and/or etc.
[0025] The RSPs 108 and 112 shown in FIG. 1 (two are shown, but one
or more are used in other systems) are the interfaces to the
satellite router 102 and the sensors. The RSPs are the point of
interaction or communication between the sensors and electronics
that support them and the satellite router 102. The sensors detect
and/or measure media, such as a state or characteristic of a gas,
aerosol, or air sample, for example, by converting the monitored or
detected characteristics of the media into data. Samples are taken
at periodic intervals to measure and record a parameter before
being converted into analog signals that are then converted into a
digital signal. In some systems, the RSPs are embedded within the
sensors, which may be embedded in unmanned aerial vehicles (UAVs),
meaning they are integrated within or a unitary part of the sensors
themselves and/or are integrated within or a unitary part of the
UAVs. Some RSPs are autonomously configured in response to the
media properties it detects, records, or others responds to and
some RSPs are configured in response to client 110 requests or
commands. The autonomous and user actuated commands dynamically
configure and control the sensors establishing when the RSPs
operate or sleep, reset, what properties or characteristics the
RSPs detect, what analysis or analytics are performed, what data is
sampled, what data is converted into digital data and stored in a
local memory and/or transmitted to the satellite router 102. Some
RSPs may generate virtual sensors as later described in FIG. 11.
Each RSP shown in FIG. 1 may transmit data in response to multiple
events: in response to a client request; when a user-defined
threshold is exceeded, at a preset or variable duty cycle, when
polled, or autonomously in real time as events occur. In this
disclosure real time relates to computer systems that process
information at least as fast as the same rate the data is received
enabling the systems to direct and control the process such as
automatically modeling and enabling sensors based on the dispersion
models. Some RSPs transmit auto-locate data identifying their
geographical areas and their operating states, and automatically
establish communication connections with the information repository
and intelligent server 106 through short data bursts when
enabled.
[0026] FIGS. 2 shows a client-side image map generated by
information repository and intelligent server 106. Regions of the
image rendered on the display may be selected by hovering over a
portion of the display, touching the display, or selecting an input
through a hand-activated input device. In FIG. 2 the image mapping
generated by server 106 shows the location and state of RSP 202
(rendered via the map tab 208). While one sensor is shown, the map
connects multiple RSP across all deployed platforms including fixed
platforms, buoyed platforms, mobile platforms: in flight, on the
road, etc.). RSP 202's color (red) indicates that the sensor is in
an inactive state or in a power saving mode such as a hibernation
mode. In hibernation mode, the content of the RSP's volatile memory
are copied to a local non-volatile storage before the RSP enters a
sleep mode. A complete list of the sensors that are part of the
system 100 may be accessed through the "Iris List" tab 206 shown in
FIGS. 2-5. And, metadata for the sensor rendered on the screen may
be accessed through a database that can be invoked when the user
selects a message tab 204. An exemplary record of the database may
identify: the station or platform it belongs to, sensor ID, its
"latitude (degree)", its "longitude (degree)", its name, its
source, its "platform type", its "start date", and/or its "end
date."
[0027] When a user hovers over the client-side image map the
information repository and intelligent server 106 renders a
statistical summary of RSP 202. The summary data shown in FIG. 3
includes identifying information; the sensors name, its latitude
(degree), its longitude (degree), weather conditions (e.g.,
temperature), communication status, and operating status, for
example. When the region of the image displaying RSP 202 is
selected the information repository and intelligent server 106
provides access to other resources linked to the RSP 202 and/or
client-side image map. Those resources include actuating a software
script or hyperlink that allows the user to control the RSP 202 or
enable autonomous control (via a plume control model, for example),
allow a user to enlarge a selected portion of the client-side image
map (e.g., provide panoramic views of its location details like a
street view), and/or directly query the RSP 202. When the RSP 202
is actuated, its visual indicator changes, such as the
representation shown in FIG. 5 where RSP is visualized in green to
indicate that RSP 202 is in an active operating state.
[0028] The system 100 models plumes and their dispersions 608 as
shown in FIG. 6. Since dispersion refers to what happens to media
after its introduction, understanding the weather patterns near it
is processed to identify and possibly control the dispersion by
enabling remediating actions. Meteorology stations 602-606 shown as
the blue icons may wirelessly transmit such information including
ground and air temperature, relative humidity, barometric pressure,
precipitation, wind and speed direction, rain amounts/snow depth,
for example, through the satellite router 102 and gateway 104 or
directly through gateway 104 to the information repository and
intelligent server 106. The Meteorology stations 602-606 may
further transmit forecast data wirelessly through the gateway 104
to the information repository and intelligent server 106.
[0029] As shown in FIG. 6, a plume modeled by the information
repository and intelligent server 106 may move away from its source
and widens because of the entrainment of the surrounding media at
or near its edges. The client-side image shown in FIG. 6 color
codes the densities of the media from a point, line, area, or
volume source. The red area represents a magnitude of concentration
higher than the yellow area, which represents a magnitude of
concentration higher than the green area, which represents a
magnitude of concentration higher than dark blue area, which
represents a magnitude of concentration higher than the light blue
area. The concentration tracer level profiles accurately predict
dispersion concentrations because it simulates dispersion events
based on local meteorological information measured or forecasted by
the meteorology stations 602-606 that are local to the source. The
inclusion of the weather data makes dispersion model more useful
and accurate than some models such as known Gaussian models because
the model does not assume that the media it is predicting has a
[0030] Gaussian distribution in changing weather conditions.
[0031] FIGS. 7 and 8 visually illustrate a three dimensional plume
dispersion model positioned at an emission source (circled in white
in FIG. 7) near weather stations (circled in blue in FIG. 7) and an
off-line RSP (circled in red in FIG. 7) on a client-side image map.
While the weather stations and RSP are shown as stationary
platforms, the weather stations and RSP may also be part of one or
more UAV's or its removable payload that may be dropped at a
location that provides precise detection, measurements, and
calculations close to the source. In FIG. 9, the projected
dispersion path and concentration levels are shown in two
dimensions with the concentration levels shown in red, pink,
yellow, green, dark blue and light blue. Finer concentration
resolutions such as those shown in high definition may be rendered
in more colors in alternative systems.
[0032] In FIG. 10 a wireless connection between the UAV 1002 the
information repository and intelligent server 106 cedes control of
the UAV 1002 from a user. In some systems short-range radar and/or
lidar sensors embedded in the UAV's 1002 keep the UAV 1002 clear of
obstacles and on track to the target 1004 by detecting approaching
objects in some cases to the millimeter and keep the UAV 1002 at
predetermined distance from the obstacles. The data is processed
on-board the UAV 1002 or alternately by the information repository
and intelligent server 106 through a wireless link that instructs
the UAV 1002 to accelerate, bank, brake, turn, etc. As shown in
FIG. 10, the UAV 1002 and the target 1004 may be tracked on a
client-side image map that may allow user intervention to assume
control or facilitate monitoring. When the target is a media
dispersion, a spiral-shaped triple-colored galaxy plume may be
rendered on the display representing the dispersion it is tracking.
As the UAV 1002 approaches the target 1004 (as shown it is 113
meters away) the UAV 1002 transmits real time updates to the
information repository and intelligent server 106 allowing it to
track all levels of concentration from the highest concentrations
of the plume at the highest to lowest levels of the plume that may
vary depending on whether the emission is a buoyant plume, a dense
plume, a passive plume, or a neutral plume. As the plume disperses
over time UAV 1002 may track the dispersion rates, dispersion
areas, and/or its respective concentrations. In some systems the
UAV 1002 may drop or position an onboard payload, such as the
payload of UAV 1002 shown in gray in response to a condition,
event, or user command at one or multiple locations.
[0033] FIG. 11 is an exemplary remote monitoring process. The
process detects media such as contaminants at 1102 through an RSP.
The RSP is the interface between the remote sensor the satellite
router that orbits the earth. Based on its configuration the RSP
transmits data to information repository and intelligent server
process that models the plume at 1104. Based on the plume model
information repository and intelligent server process activates and
configures mobile and static intelligent sensors that are a part of
the RSP at 1008. In some alternative processes, the information
repository and intelligent server process may create a virtual
sensor through a virtual configuration file. The virtual sensor
configuration file may define one or more of the input parameters
the virtual sensor should meter or measure, the analytic to be
performed, the output to be returned, and/or the port number where
the output data is to be transmitted. Based on the virtual
configuration file, an RSP may dynamically search, identify, and
connect a sensor plug-in accessed locally through the RSP memory or
remotely through a local wireless Internet Service Provider (ISP)
or satellite router that may access a local area network library of
sensor plug-ins. Once functional, the RSP and virtual sensor may
stream the output to the information repository and intelligent
server process.
[0034] If contaminates are shown or forecasted to spread through
weather data and the plume models, the process enables, configures,
and/or generates additional RSPs and/or sensors that can track and
forecast the path and the flow rates of the gases and aerosols that
may comprise the plumes in a predicted area. As the plume spreads
or is projected to spread to an area the process activates and
configures sensors at 1112 and 1108 in the projected contaminants
paths (its geographic areas), harvests data from RSPs, and
meteorological stations in or near its path automatically or
through polling, and adjusts the plume model based on the newly
harvested data to help identify the gases and aerosols (or other
media), their respective concentrations, and the paths and rates
that it will flow. The processes RSPs/sensors/virtual sensors and
operations can match the real time characteristics of an event
allowing the event to respond to one or more dispersions as it
occurs (e.g., at least at the same rate data is received),
creating, enabling, and/or positioning RSP's (e.g., through UAVs or
mobile platforms) in projected paths, disabling RSP's or removing
virtual plug-in sensors from RSPs that are no longer needed or are
not within the projected plume path, while making corrections and
enabling other sensors based on measurements, analytics, and
forecasts.
[0035] While the communication between the RSPs and the satellite
router and the ISP's may occur through packets through a packet
switched protocol like a Transmission Control Protocol\Internet
Protocol (TCP/IP) type Internet protocol, alternative communication
protocols are used in alternate systems and processes. One
alternate uses a modified linear network coding, which improves
wireless bandwidth by an order of magnitude without adding base
stations, routers, or spectrum. The modified linear network coding
transforms the communication exchange by not resending packets that
may be dropped or do not arrive at a destination. Instead of
re-sending packets this alternate communication protocol transmits
linear algebraic equations that describe the functional
relationship between series of packets (two or more packets that
are transmitted consecutively in some systems/processes and
nonconsecutively in alternate systems/processes) so that when a
packet does not arrive, the receiving device or process processes
the algebraic equation to recreate the missing packet at the
client-receiving device. Since the equation is an algebraic
equation describing the relation between segments of packets, the
load on the receiving client device is negligible. In an exemplary
application coded packets are encoded using random linear network
coding. The coded packets are encoded using an earlier sequenced
packet and randomly generated coefficients, using a linear algebra
function. The combined packet length is no longer than either of
the two or more packets from which it is composed. When a packet is
lost, the missing packet is mathematically derived from a
later-sequenced packet that includes earlier-sequenced packets and
the coefficients used to encode the packet. In yet another
alternate communication system or process, the transmitting device
may combine several packets into one same-sized packet using random
linear coding. The same number of packets may be sent or received
as would occur in normal TCP/IP type protocol. However, if a packet
does not arrive at a destination the random linear coding in this
alternate re-generates the original stream based on the packets
interchangeability. The second alternative communication system
significantly reduces the packets resent and the associated
signaling needed to track the lost packets. Both exemplary
protocols are stateless data transmissions that achieve higher
speeds without link layer flow control slowing down the exchanges
with retransmission requests. The systems/processes apply a
mathematical approach to data error correction and data
transmission redundancy.
[0036] FIG. 12 illustrates a second alternate global plug-and-play
automated configurable sensor control and data acquisition
platform. In this second alternate system the mapping software
(that generates the client-side image maps), the data visualization
software (that graphically/visually displays plume models and
weather models), the plume modeling engine (that generates the
plume models), the remote system control logic (that
activates/configures and/or generates the sensors on the RSPs) and
the processing of the weather data occur on the client device
12-110, while the state monitoring and control and logging software
(that writes the log files) occurs on the information repository
and intelligent server 12-106. FIG. 13 illustrates a third global
plug-and-play automated configurable sensor control and data
acquisition platform. In this third alternate system the hardware
satellite router 102 of FIG. 1 is replaced with an ISP hardware
interface to the Internet 1302, the hardware information repository
and intelligent server 106 is moved to a cloud computing platform,
and the RSP data is supplemented with local weather station data
collected from a UAV or ground station, other ground station data,
and UAV transmitted data at the alternate client device 13-110.
FIG. 14 is an exemplary RSP deployment that may provide global
control from a connected device. And, FIG. 15 is an exemplary RSP
reduced to practice.
[0037] The methods, devices, systems, and logic described above may
be implemented in many different ways in many different
combinations of hardware, software or both hardware and software.
For example, in some modes of operation the mapping and data
visualization on the client side devices may generate the
client-side image maps that identify when RSPs report a detection
(e.g., a hit) in real time. The real time reporting and rendering
on the client side maps may visualize one or more dispersions as
they occur. In another mode of operation, the remote system control
logic may actuate all of the RSPs in communication with the client
device at once to detect and render visualizations of the
dispersions as they occur. The methods, devices, systems, and logic
described above may make use of many types of dispersion models as
well as hybrids of one or more dispersion models including:
Lagrangian models, Eulerian models, dense gas models, box models,
Gaussian models, etc. The models may represent one or more buoyant
plumes, dense gas plumes, passive and/or neutral plumes, etc.
[0038] All or parts of the system may comprise one or more
controllers, one or more microprocessors (CPUs), one or more signal
processors (SPU), one or more graphics processors (GPUs), one or
more application specific integrated circuit (ASIC), one or more
programmable media or any and all combinations of such hardware.
All or part of the logic, specialized processes, and systems
described may be implemented as instructions for execution by
multi-core processors (e.g., CPUs, SPUs, and/or GPUs), controller,
or other processing device including exascale computers and compute
clusters, and may be displayed through a display driver in
communication with a remote or local display, or stored in a
tangible or non-transitory machine-readable or computer-readable
medium such as flash memory, random access memory (RAM) or read
only memory (ROM), erasable programmable read only memory (EPROM)
or other machine-readable medium such as a compact disc read only
memory (CDROM), or magnetic or optical disk. Thus, a product, such
as a computer program product, may include a storage medium and
computer readable instructions stored on the medium, which when
executed in an endpoint, computer system, or other device, cause
the device to perform operations according to any of the process
descriptions or hardware descriptions above.
[0039] The systems may be implemented through processors (e.g.,
CPUs, SPUs, GPUs, etc.), memory, interconnect shared and/or
distributed among multiple system components, such as among
multiple processors and memories, including multiple distributed
processing systems. Parameters, databases, software and data
structures used to evaluate and analyze these systems or logic may
be separately stored and managed, may be incorporated into a single
memory or database, may be logically and/or physically organized in
many different ways, and may be implemented in many ways, including
data structures such as linked lists, programming libraries, or
implicit storage mechanisms. Programs may be parts (e.g.,
subroutines) of a single program, separate programs, application
program or programs distributed across several memories and
processor cores and/or processing nodes, or implemented in many
different ways, such as in a library, such as a shared library. The
library may store virtual sensor configuration files that may
generate micro sensor plug-ins as described herein. The virtual
sensors may be generated dynamically, and in real-time which may
include for example, configuring devices on the RSP's such as a
spectrometer comprising a light source and camera that may be part
of some RSP's or UAV's. The software makes use of the RSP's camera
to image spectra of a source by capturing an images and comparing
the underlining emission lines that are captured to a library of
emission lines stored in a memory. By measuring the electromagnetic
spectrum a source absorbs or emits, the virtual sensor can
determine the molecular composition of the source/target. A virtual
sensor may also enable accelerometers on the RSPs, for example,
that can measure the rate of change of velocity and detect the
orientation of the RSP or UAV, should the RSP or UAV change
positions. The RSPs may also communicate with some or every active
sensor and plug-in sensor and collect data from the external and
internal sensors too. Once the RSP gathers all of the information,
it generates a file that may be autonomously transmitted (e.g., an
asynchronous transmission) or transmitted on demand. While various
embodiments have been described, it will be apparent to those of
ordinary skill in the art that many more embodiments and
implementations are possible.
[0040] The term "coupled" disclosed in this description may
encompass both direct and indirect coupling. Thus, first and second
parts are said to be coupled together when they directly contact
one another, as well as when the first part couples to an
intermediate part which couples either directly or via one or more
additional intermediate parts to the second part. The term
"substantially" or "about" encompass a range that is largely
(ninety five percent or more), but not necessarily wholly, that
which is specified. It encompasses all but a significant amount.
When devices are responsive to or occur in response to commands
events, and/or requests, the actions and/or steps of the devices,
such as the operations that devices are performing, necessarily
occur as a direct or indirect result of the preceding commands,
events, actions, and/or requests. In other words, the operations
occur as a result of the preceding operations. A device that is
responsive to another requires more than an action (i.e., the
device's response to) merely follow another action.
[0041] While various embodiments of the invention have been
described, it will be apparent to those of ordinary skill in the
art that many more embodiments and implementations are possible
within the scope of the invention. Accordingly, the invention is
not to be restricted except in light of the attached claims and
their equivalents.
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